eXtreme Transaction Processing

Massimo Pezzini, distinguished Gartner Analyst coined the term eXtreme Transaction Processing or XTP in 2007.  XTP relates to a class of applications that requires collecting, correlating, and operating on large volumes of data to deliver meaningful insights into business use cases.  Data processed by these XTP applications comes in the form of large numbers of events, and represents data that changes frequently.  When conventional OLTP/ETL systems becomes bottlenecks as they cannot provide high-speed performance and are unable to scale elastically on demand, XTP application helps to solve business problems like online trading, risk assessment, and fraud detection.

For high-speed performance in-memory data grids (IMDG) are used that overcomes both disk I/O and network I/O. They are distributed across nodes with micro-second latency. IMDG avoids network hops by optimizing data distribution and replication. It is similar to MapReduce of Hadoop but is in real-time. They also can distribute transactions, queries, and procedures at a low-latency response times. Thus it provides both elastic scaling on demand and high-speed performance. NoSQL or NewSQL can be used with IMDGs. NoSQL provides API and functions to programmatically access key-values, objects, and more. NewSQL uses SQL on structure data – that is for data that require XTP with ACID guarantees.

Pivotal GemFire is an in-memory NoSQL data grid that can handle XTP with high throughput, high scalability, and low latency. It also comes with Spring integration and simplified APIs for greater development ease. GemFire’s event driven architecture and continuous querying can also send selected events to other systems like complex event processing platforms.

Pivotal SQLFire is an in-memory NewSQL grid that handles XTP with fast-throughput, low latency, high scalability and a consistent view of data. SQLFire also supports global WAN connectivity and provides the option of replicating data to remote clusters for disaster recovery.

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